神经元建模。顶叶皮层中的单次试验尖峰序列揭示了决策过程中的离散步骤。
NEURONAL MODELING. Single-trial spike trains in parietal cortex reveal discrete steps during decision-making.
作者信息
Latimer Kenneth W, Yates Jacob L, Meister Miriam L R, Huk Alexander C, Pillow Jonathan W
机构信息
Center for Perceptual Systems, The University of Texas at Austin, Austin, TX 78712, USA. Institute for Neuroscience, The University of Texas at Austin, Austin, TX 78712, USA.
Institute for Neuroscience, The University of Texas at Austin, Austin, TX 78712, USA. Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA.
出版信息
Science. 2015 Jul 10;349(6244):184-7. doi: 10.1126/science.aaa4056.
Neurons in the macaque lateral intraparietal (LIP) area exhibit firing rates that appear to ramp upward or downward during decision-making. These ramps are commonly assumed to reflect the gradual accumulation of evidence toward a decision threshold. However, the ramping in trial-averaged responses could instead arise from instantaneous jumps at different times on different trials. We examined single-trial responses in LIP using statistical methods for fitting and comparing latent dynamical spike-train models. We compared models with latent spike rates governed by either continuous diffusion-to-bound dynamics or discrete "stepping" dynamics. Roughly three-quarters of the choice-selective neurons we recorded were better described by the stepping model. Moreover, the inferred steps carried more information about the animal's choice than spike counts.
猕猴顶内沟外侧区（LIP）的神经元在决策过程中表现出放电率似乎向上或向下倾斜的现象。这些倾斜通常被认为反映了朝向决策阈值的证据逐渐积累。然而，试验平均反应中的倾斜可能反而源于不同试验在不同时间的瞬时跳跃。我们使用用于拟合和比较潜在动态脉冲序列模型的统计方法研究了LIP中的单试验反应。我们比较了具有由连续扩散到边界动态或离散“步进”动态控制的潜在脉冲率的模型。我们记录的大约四分之三的选择选择性神经元用步进模型能更好地描述。此外，推断出的步幅比脉冲计数携带了更多关于动物选择的信息。
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